1. Field of Invention
The invention relates to a method and apparatus for computation of products of a vector and a sequence of matrices.
2. Description of Related Art
Vector matrix products occur often in applications such as speech recognition, signature verification, error correction code decoding, etc. Techniques such as the forward-backward-algorithm (FBA) are commonly used for such applications. However, equipment that performs these algorithms requires large amounts of memory for storing all the matrices and intermediate matrix products needed to support these algorithms.
For example, when Hidden Markov Models (HMM) are applied to describe a communication channel, products of sequences of probability density matrices are needed to estimate the a posteriori probabilities of transmitted symbols given the received symbols. The FBA requires that the sequence of matrices multiplied by the first vector in a recursive manner in the forward part of the algorithm to be stored in memory and the decoding process can start only after a long sequence of symbols has been received. This is intolerable in many applications (a telephone application, for example) which impose strict constraints on the message delivery delay. Thus, new technology is needed to improve the vector-matrix product calculation which enables a decoder to estimate the product without waiting for the whole sequence to be received. This technology enables a designer to trade the product estimation accuracy for smaller delays in information delivery.